The Department of Adaptive Systems focuses predominantly on the design of decision-making systems, which modify their behavior according to the changing properties of their environment. This essential ability – adaptivity – enhances their efficiency. Decades of research have brought a number of conceptual, theoretical, algorithmic, software and application results. The applicability of adaptive systems is currently being extended toward complex scenarios by improving the classical adaptive systems and by developing their new versions.

The departmental “know-how” serves to resolve national as well as international research projects, running in collaboration with industry and government agencies. The interplay between theory and limited computing power is the common issue linking the various project domains. They include traffic control, management and control of technological systems, radiation protection, nuclear medicine, analysis of financial data, electronic democracy, etc. The increasing complexity of the problems addressed directs the main stream of the research toward decentralized control of large-scale systems and normative decision-making with multiple participants.

Last events:

The 2011 Outstanding Statistical Application Award of American Statistical Association has been presented to Miroslav Kárný and his co-authors A. Raftery (University of Washington) and P. Ettler (Compureg s.r.o.). This award recognises "extending Bayesian methods for model uncertainty to temporally evolving systems and showing how these ideas can be successfully applied to solving a challenging problem in a continuous manufacturing system."

Miroslav Kárný and his co-authors A.Raftery (University of Washington) and P.Ettler (Compureg s.r.o.) were selected to receive the Frank Wilcoxon Prize for their paper: “Online prediction under model uncertainty via dynamic model averaging: application to a cold rolling mill” that appeared in the February 2010 issue of Technometrics. The Wilcoxon Prize is given to the best practical application paper appearing in the previous year's Technometrics.